Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 13, Issue 4, 2016, Pages 643-655

  Catanzaro, Daniele ^a   Shackney, Stanley E ^b   Schaffer, Alejandro A ^c   Schwartz, Russell ^d  

^a LOUVAIN SCHOOL OF MANAGEMENT   (Belgium)

^b DREXEL UNIVERSITY COLLEGE OF MEDICINE   (United States)

^c NATIONAL INSTITUTES OF HEALTH   (United States)

^d CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

combinatorial optimization; computational biology; distance methods; ductal carcinoma of the breast; mixed integer linear programming; network design; parsimony criterion; phylogeny estimation; single cell sequencing; Tumor profiling

Indexed keywords

BIOLOGY; COMBINATORIAL OPTIMIZATION; DIAGNOSIS; TUMORS;

COMPUTATIONAL BIOLOGY; DISTANCE METHOD; DUCTAL CARCINOMA; MIXED INTEGER LINEAR PROGRAMMING; NETWORK DESIGN; PARSIMONY CRITERION; SINGLE CELLS; TUMOR PROFILING;

INTEGER PROGRAMMING;

ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; BREAST NEOPLASMS; CARCINOMA, DUCTAL; CLONAL EVOLUTION; CLUSTER ANALYSIS; FEMALE; GENETICS; HUMAN; PATHOPHYSIOLOGY; PROCEDURES;

ALGORITHMS; BREAST NEOPLASMS; CARCINOMA, DUCTAL; CLONAL EVOLUTION; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; FEMALE; HUMANS; MODELS, GENETIC;

EID: 84982204058     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2015.2476808     Document Type: Article

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